TROUBLESHOOTING REPRODUCTIVE PROBLEMS:
WHERE TO BEGIN AND WHAT TO EXPECT
J.C. Dalton* and A. Ahmadzadeh†
University of Idaho
Caldwell Research and Extension Center*
Animal and Veterinary Science Department, Moscow†
Trends in Reproductive Performance
Reproductive performance in Idaho and Utah dairy herds has declined steadily over the
last decade. According to records processed through DHI-Provo for the period 1993 to 2002,
average days open has increased by 30 and 42 days for Idaho and Utah dairy herds, respectively.
Multiple factors have likely contributed to the increase in average days open. Further review of
DHI-Provo records reveals a decrease in the first service conception rate, coupled with increases
in average days to first breeding, the number of services per conception, and the estimated
percentage of missed heats for Idaho and Utah dairy herds (Table 1).
Table 1. Trends in reproductive performance of Idaho and Utah
dairy herds for the period 1993 to 2002. (Source: DHI-Provo).
Year
Item
1993
2002
Idaho
First service conception rate, %
55
41
Days open
134
164
Average days to first breeding
86
86
Services per conception
1.88
2.55
Estimated missed heats, %
32
39
Utah
First service conception rate, %
52
44
Days open
132
174
Average days to first breeding
84
94
Services per conception
1.89
2.28
Estimated missed heats, %
32
47
The failure to detect estrus in a timely and accurate manner is often cited as the most
common and costly problem of AI programs. Consequently, heat detection is the major factor
limiting reproductive performance on many dairy farms. Other factors limiting reproductive
performance include inadequate management of cattle during the transition period (late dry
period and early postpartum), and genetic selection for high milk production.
Clearly, reproductive performance of Idaho and Utah dairy herds is a problem. It is
apparent that variability in production level, herd size, and housing may not be conducive to the
implementation of standard operating procedures for reproductive management. As a result,
there may be diverse reproductive management strategies for different herd situations.
Nevertheless, practical steps can be taken to enhance reproductive efficiency of all dairy herds
regardless of production level, herd size, and housing.
Troubleshooting Reproductive Problems: Where do I begin?
Records Analysis
Generally, the reason a consultant or extension specialist is called to troubleshoot
reproductive problems is because the dairy producer, nutritionist, or veterinarian has noticed a
decline in reproductive efficiency in the herd. Accurate records provide the starting point for
troubleshooting reproductive problems.
Stratification of records by lactation number (first lactation, second lactation, and third
lactation and greater) is necessary to allow for greater sensitivity in determining if a particular
lactation group may have reproductive problems. Before evaluating a herd’s reproductive status it
is important to understand the components of each reproductive performance measurement. Then
the most meaningful measurements can be used to evaluate, develop, and monitor management
strategies to improve the reproductive performance of the herd.
Pre- and post-service heat detection efficiency. The single most important factor that
impacts reproductive efficiency is heat detection. Heat detection is important throughout
lactation, especially in the following three areas: 1) prior to the end of the voluntary waiting
period (typically between 45 to 60 days after calving), 2) within the first 21 days of the end of
the voluntary waiting period, and 3) 18 to 24 days after each insemination, (the time frame in
which a cow, if open to a previous insemination, should return to heat). Pre-service heat
detection includes the heat detection that occurs between calving and the first service that a cow
receives. Pre-service heat detection is important so that a future breedable heat may be
anticipated, and anestrus cows may be identified and treated. Low pre-service heat detection
efficiency may be related to problems such as dystocia, milk fever, ketosis, displaced abomasum,
retained placenta, and severe loss of body condition. Most healthy dairy cows will show at least
one heat prior to 60 days in milk. Post-service heat detection includes the heat detection that
occurs between the time of first service and determination of pregnancy. Low post-service heat
detection efficiency may be an indication of a lack of attention to cows having received a
service. Pregnancy checks should occur, on average, 35 to 40 days after breeding. This will
ensure open cows are recognized prior to 42 days after breeding (two estrous cycles). Examples
of calculations of pre- and post-service heat detection efficiency are shown in Figures 1 and 2.
Pre- and post-service heat detection efficiency should be 70% or greater.
Days to first service. Days to first service (also known as days in milk at first service,
days in milk at first breeding) is an excellent indicator of management of the herd through the
dry period, calving, and early lactation. Cows in poor body condition (either too fat or too thin)
during these critical periods will have a greater tendency toward calving difficulties and
metabolic disorders, and will be slower to return to estrus. Days to first service is also directly
related to pre-service heat detection efficiency. The better the pre-service heat detection
efficiency, the greater the number of cows that should receive first service within the first 21
days following the voluntary waiting period. Average days to first service should be within 11
days and not more than 21 days of the end of the voluntary waiting period. For example, with a
60-day voluntary waiting period, average days to first service should be 71 and not more than 81.
Formula:
Days in an estrous cycle
X 100 = pre-service heat
detection efficiency
(DFS – VWP) + 11
Example:
VWP:Voluntary waiting period
DFS: Days to first service
Days in an estrous cycle
Half an estrous cycle
60 days
92 days
21 days
11 days
Calculation:
21
X 100 = 48.8%
(92 – 60) + 11
Figure 1. Calculating pre-service heat detection efficiency. The use of 11 in the formula
assumes that the first breedable heat beyond the voluntary waiting period of 60 days would be
detected on average, by 71 days in milk. (Source: Bailey et al., 1998)
Information required
Average days open
Days to first service
Days in one estrous cycle
Services per conception
159
92
21
2.3
Calculation
1. Average days open – days to first service = cow eligible heat days
159 – 92 = 67
2. Cow eligible heat days  an estrous cycle = potential heats missed
67  21 = 3.2
3. Services per conception – 1 (service the cow became pregnant) =
number of remaining services
2.3 – 1 = 1.3
4. Number of remaining services  potential heats missed ( 100) =
post-service heat detection efficiency
(1.3  3.2)  100 = 41%
Figure 2. Calculating post-service heat detection efficiency. (Source: Bailey et al., 1998)
Conception rate. Conception rate is directly related to the number of services per
conception (also called services per pregnancy). To estimate the conception rate of the herd,
divide 100 by the services per conception. For example, if the herd averages 2.5 services per
conception, this translates into a 40% conception rate. Services per conception should be less
than 2.0 for lactating cows, which translates into a conception rate of 50% or greater.
Pregnancy rate. Pregnancy rate may be defined as the percentage of cows eligible to
become pregnant within a given interval (21 days, the typical length of an estrous cycle, or 7 days,
the length of a week), that actually do become pregnant. For example, if you have 100 cows that
are past the voluntary waiting period (therefore they are pregnancy eligible), and 20 cows
become pregnant during one 21-day period, then the pregnancy rate is equal to 20%. By dividing
the breeding program into 21-day intervals, you can determine the effect of recent events or
management changes on reproductive efficiency. This definition of pregnancy rate provides a
method to monitor the rate at which cows become pregnant. If the pregnancy rate is low, the
average days in milk for the herd will be high. Consequently, the herd will have a lower average
milk production because a lower than desirable percentage of the herd will be in early lactation,
while a higher than desirable percentage of the herd will be in late lactation. In data compiled by
Niles et al. (2001), the overall AI pregnancy rate for 83 California herds (100,000 cows) ranged
from 8% to 26%, with an average of 16%. Pregnancy rate should be greater than 25%.
Calving interval. Calving interval is influenced by the voluntary waiting period, heat
detection rate, conception rate, days open, herd health, and gestation interval. Calving interval is
typically a historical measurement. Therefore, calving interval is an indicator of past
reproductive performance, but doesn’t describe the herd’s current status, as it is not very
sensitive to change. Furthermore, it is possible for a herd to have an “acceptable” calving
interval even when reproductive problems exist. For example, one cow with a calving interval of
15 months and three cows with an 11-month interval results in an average of a 12-month calving
interval. None of these calving intervals are desirable. Dairy cattle should calve at a 12.5 to 13month interval.
Average days open. Average days open is also a historical measurement that is not very
sensitive to change. Days open is influenced by the voluntary waiting period, heat detection rate,
conception rate, and herd health. The cost of excessive days open (due to decreased milk
production and increased veterinary and breeding costs) has been estimated at $1.00 to $3.00 per
cow for each day past 90 days in milk. To achieve a calving interval of 12.5 to 13 months, cattle
must conceive within approximately 120 days after calving. Therefore, average days open should
be 120 days or less.
The Transition Period (The Late Dry Period and The Early Fresh Period)
Factors negatively influencing the resumption of cyclicity include drastic changes in body
condition during the dry period and early postpartum, time required for uterine involution and
repair, milk fever, retained placenta, metritis, ovarian cysts, ketosis, displaced abomasum, ruminal
acidosis, and lameness. It is imperative for producers to implement effective dry and transition cow
management programs to prevent these problems. Should they occur, producers must treat them as
quickly as possible and re-evaluate their dry and transition cow management programs. Typically,
cows that experience a postpartum problem will have 50% lower conception rates than that of
normal cows (Lucy, 2001). Therefore, the next logical step in troubleshooting reproductive
problems is a meeting with the dairy owner (or manager) and the herd’s nutritionist.
Dairy cattle experience negative energy balance during early lactation. The magnitude and
duration of negative energy balance depends more on feed (dry matter) intake than milk yield.
Several investigators have hypothesized that the severity of negative energy balance delays the
resumption of the first postpartum ovulation (Lucy, 2001;Butler, 2000). The severity of postpartum
negative energy balance and the delay in the initiation of normal postpartum reproductive cyclicity
is associated with body weight and body condition loss (Britt, 1992). The existence of this
relationship makes body condition scoring (BCS) a useful management tool for evaluating
reproductive performance relative to nutritional status. Britt (1992) reported that high producing
Holstein cows that lost body condition dramatically (> 0.5 point on a scale of 1 to 5) during the
first 5 weeks postpartum had longer intervals to first ovulation, a lower first service conception
rate, and overall lower conception rates. Researchers in Florida (Moreira et al., 1998) have shown
that the pregnancy rate to timed AI was approximately 12% lower for cows with a BCS less than
2.5, compared to those with a BCS greater than 2.5, on a scale of 1 to 5. Therefore, during the
meeting with the dairy owner (or manager) and the herd’s nutritionist, the transition program
should be evaluated, including a walk-through of the herd to evaluate body condition. On a
scale of 1 to 5, dairy cattle should calve with a BCS of 3.5, be between 2.75 and 3.0 at 30 days in
milk, and be no lower than 2.5 between 30 and 100 days in milk.
Heat Detection and AI
Critically evaluate the heat detection program after reviewing the transition cow
management program. The failure to detect estrus is the most common and costly problem of AI
programs and the major limiting factor of reproductive performance on many dairy farms (Nebel
and Jobst, 1998). Nevertheless, reproductive problems are seldom due to a single cause.
As dairy herds increase in size, employees devote less time per cow. Consequently, many
dairy farms rely on heat detection aids such as tail chalk to allow personnel to determine which
cows are in heat based on secondary signs. To improve reproductive efficiency, herd managers
and AI technicians must pay strict attention to the details of heat detection (correct cow
identification and accurate record keeping). Chalk must be refreshed everyday. Cows that are
eligible to be bred should be marked differently than pregnant or recently fresh cows. If cows
are detected in heat, the herd manager or AI technician should check the cows’ record before
insemination occurs. Greater emphasis should be placed on detecting heats prior to the end of the
voluntary waiting period so that future heats may be anticipated and anestrous cows may be
identified.
With less time devoted per cow, a heat detection plan must be designed that is time and
labor efficient. “Set-up” prostaglandin shots during the voluntary waiting period ensure that
cattle are grouped together for greater heat detection and AI labor efficiency after the end of the
voluntary waiting period. The greater the number of animals in heat simultaneously (termed a
“sexually active group”), the greater the opportunity for AI personnel to achieve success. Keep in
mind that prostaglandin shots will only be effective in cows that are cycling. “Set-up”
prostaglandin shots are also a vital component of Presynch+Ovsynch and Modified Targeted
Breeding programs.
Systematic Breeding Programs
After evaluation of the heat detection program, consider the use of a systematic
breeding program (Presynch+Ovsynch or Modified Targeted Breeding) to provide an
organized and efficient approach to administering AI. Several pharmaceuticals including
gonadotropin releasing hormone (e.g. Fertagyl®, Cystorelin®, Factrel®) and prostaglandin
F2alpha (PGF; e.g. Lutalyse®) are used to control the timing of ovulation or estrus through
manipulation of follicular growth and (or) by altering the length of the estrous cycle. Systematic
breeding programs allow for efficient and convenient AI because they either make the
occurrence of estrus more predictable or allow for timed AI without estrus detection.
Conception rates resulting from these protocols vary. Therefore, it is difficult to prescribe a
single protocol for all dairy farms. Nevertheless, there are common factors among all systematic
breeding protocols that should be practiced the same on all farms. These factors include drug
dosages, time of administration, route of administration, time of insemination, and cow
identification.
Systematic breeding protocols result in many cows receiving AI on the same day.
Therefore, it is imperative the dairy has adequate facilities and experienced AI personnel. AI
personnel should not thaw more straws than can be inseminated within 10 to 15 minutes. A
review of proper semen handling procedure must occur with AI personnel whether a systematic
breeding protocol is implemented or not. Peters et al. (1984) reported that cervical insemination
errors accounted for approximately 20% of attempted uterine body depositions, while
Macpherson (1968) reported that cervical insemination resulted in a 10% decrease in fertility
when compared with deposition of semen in the uterine body. Clearly, all AI technicians must
develop sufficient skill to recognize when the tip of the AI gun remains in the cervix. To
maximize conception rates, AI technicians must continue to manipulate the reproductive tract
until the tip of the AI gun is past the cervix and deposition into the uterus can be accomplished.
Troubleshooting Reproductive Problems: What should I expect?
Reproductive management is a continuous process. Measuring reproductive performance is
of little value if goals are not set and strategies to increase reproductive efficiency developed and
monitored. Specific causes of reproductive inefficiency may be difficult to identify, are seldom due
to one cause, and may be difficult to resolve. All dairy employees must work as a team to achieve
the goals of any management program, whether it concerns milking, nutrition and health, or
reproduction.
When evaluating the success (or failure) of a new reproductive management program, it
is important to remember that traditional reproductive indices such as average days open and
calving interval are not very sensitive to change. Consequently, even though progress is being
made due to the implementation of new management programs, these reproductive indices may
not change significantly for months. In contrast, pregnancy rate (21-day or 7-day) is sensitive to
change. As mentioned previously, pregnancy rate allows for the evaluation of recent events or
management changes on reproductive efficiency. Realistically, pregnancy rate should be greater
than 20 %, with a goal of exceeding 25%.
If a systematic breeding protocol was implemented, conception rate per AI offers an
easily calculated snapshot of success. If 10 cows received timed AI on the Ovsynch protocol, and
4 were later determined to be pregnant from the timed AI, the conception rate per AI equals
40%. With the advent of timed AI protocols, more cows are inseminated in a short period of time
and, hopefully, more cows will become pregnant earlier in lactation. Immediately following
pregnancy examination, dairy producers should pay more attention to those cows that have not
conceived to AI. It is apparent that in all systematic breeding programs, the conception rate at
first AI will not reach 100%. Therefore, cows will need to be inseminated a second or third time
in order to become pregnant. Producers should pay close attention 18 to 24 days after AI to
detect cows that return to estrus.
In summary, reproductive management is critical to profitability of a dairy.
Unfortunately, reproductive efficiency has declined steadily in Idaho and Utah dairy herds. As
multiple factors have likely contributed to the decline in reproductive efficiency, management
strategies to increase reproductive performance may also be multi-factorial, including 1)
increased attention to a) heat detection efficiency (pre- and post-service), and b) pregnancy rate,
2) evaluating and monitoring body condition scores (throughout lactation and the dry period), 3)
implementing a transition cow program, with the goals of decreasing a) the severity and duration
of negative energy balance, and b) the incidence of postpartum health problems, 4) implementing
a systematic breeding program, and 5) practicing proper semen handling. Over time traditional
measures such as average days open and calving interval will change as a result of the success of
the new management program. More importantly, success may be revealed earlier through the
monitoring of pregnancy rate (21-day or 7-day), and in timed AI programs by conception rate per
AI.
References
Bailey, T.L., Murphy, J.M., and Dascanio, J. 1999. Analyzing reproductive records to improve
dairy herd production. In: Veterinary Medicine, pp. 269-276.
Britt, J. H. 1992. Impact of early postpartum metabolism on follicular development and fertility.
New concepts in the interactions of nutrition and reproduction. In: Bovine Proceedings, p. 39.
Butler, W. R. 2000. Nutritional interactions with reproductive performance in dairy cattle.
Animal Reproduction Science 60-61:449-457.
Lucy, M. C. 2001. Reproductive loss in high-producing dairy cattle: where will it end? Journal
of Dairy Science 84:1277-1293.
Macpherson, J.W. 1968. Semen placement effects on fertility in bovines. Journal of Dairy Science
51:807-808.
Moreira, F. C., Risco, M.F.A., Ambrose, J.D., Morset, M., Delorenzo, M. and Thatcher, W.W.
1998. Effect of body condition on reproductive efficiency of lactating dairy cows receiving a timed
insemination. Journal of Dairy Science 81:(Suppl 1):215.
Nebel, R. L. and Jobst, S.M. 1998. Evaluation of systematic breeding programs for lactating
dairy cows: a review. Journal of Dairy Science 81:1169-1174.
Niles, D., Eicker, S., and Stewart, S. 2001. Using pregnancy rate to monitor reproductive
management. In: Proceedings of the 5th Western Dairy Management Conference, Las Vegas,
NV, pp. 117-122.
Peters, J.L., Senger, P.L., Rosenberger, J.L. and O’Connor, M.L. 1984. Radiographic evaluation of
bovine artificial inseminating technique among professional and herdsman-inseminators using .5and .25-mL French straws. Journal of Animal Science 59:1671-1683.